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Big 4 Firm Risk & Workload Analysis
Finance & Banking Analytics
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About
Offers in-depth insights into financial risk assessment, compliance violations, and fraud detection trends within the Big 4 consulting firms – Ernst & Young (EY), PwC, Deloitte, and KPMG – spanning from 2020 to 2025. It details key metrics such as the number of audit engagements, high-risk cases, detected fraud cases, and compliance breaches. Additionally, the data explores the influence of AI in auditing processes, employee workload, and client satisfaction scores. This information is highly relevant for finance professionals looking to analyse trends in financial compliance, audit effectiveness, and corporate risk, as it allows for cross-sector comparisons.
Columns
- Year: The year of the audit report, ranging from 2020 to 2025.
- Firm_Name: The name of the consulting firm performing the audit, including Ernst & Young, PwC, Deloitte, and KPMG.
- Total_Audit_Engagements: The total number of audit engagements handled by each firm.
- High_Risk_Cases: The count of audits identified as high-risk due to significant compliance concerns.
- Compliance_Violations: The number of detected regulatory breaches.
- Fraud_Cases_Detected: The count of fraud cases uncovered during the auditing processes.
- Industry_Affected: The specific sector impacted by the audit findings, such as Finance, Tech, Retail, or Healthcare.
- Total_Revenue_Impact: The estimated financial impact, in millions USD, resulting from fraud or compliance issues.
- AI_Used_for_Auditing: A boolean indicator (Yes/No) of whether Artificial Intelligence was utilised in the auditing process.
- Employee_Workload: The average weekly working hours for auditors.
- Audit_Effectiveness_Score: A score reflecting the effectiveness of the audit.
- Client_Satisfaction_Score: A score representing client satisfaction with the audit services.
Distribution
The dataset is provided as a CSV file, with a size of 5.94 kB and comprises 12 columns. Most columns contain 100 valid entries, with no missing or mismatched data. The data captures trends over a specific period and has an expected update frequency of 'Never'.
Usage
This dataset is ideal for financial analysts, auditors, data scientists, and risk managers. It can be used to analyse trends in financial compliance, evaluate audit effectiveness, and assess corporate risk across the Big 4 firms. Users can explore the impact of AI on risk detection and compliance, conduct industry comparisons (Finance, Tech, Retail, Healthcare), and investigate the relationship between auditor workload and compliance quality.
Coverage
The data covers the period from 2020 to 2025. It focuses on the Big 4 consulting firms: Ernst & Young, PwC, Deloitte, and KPMG. The industries included in the analysis are Finance, Tech, Retail, and Healthcare.
License
CC0: Public Domain
Who Can Use It
- Financial Analysts: For trend analysis in financial compliance and risk.
- Auditors: To understand audit effectiveness and the impact of AI on their work.
- Data Scientists: For modelling risk detection and compliance patterns.
- Risk Managers: To assess corporate risk and identify high-risk cases.
- AI Researchers in Finance: To study the application and impact of AI in auditing.
- Finance Professionals: For general insights into Big 4 consulting firm performance and compliance quality.
Dataset Name Suggestions
- Big 4 Financial Risk & Fraud Insights 2020-2025
- Consulting Audit Performance Metrics
- AI in Auditing: Big 4 Trends
- Corporate Financial Compliance Data
- Big 4 Firm Risk & Workload Analysis
Attributes
Original Data Source:Big 4 Firm Risk & Workload Analysis
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